mlb-player-analyzer
Deep-dive analysis of a single MLB player (hitter or pitcher) for the Yahoo Fantasy Baseball 2K25 league. Web-searches FanGraphs (ATC projections), Baseball Savant (xwOBA/xBA/xERA), MLB.com (lineups, probables), RotoWire (weather, injuries), and RotoBaller (closer depth) to produce the full set of structured player signals defined in the signal framework. Emits form_score, matchup_score, opportunity_score, daily_quality, regression_index, obp_contribution, sb_opportunity, role_certainty for hitters and qs_probability, k_ceiling, era_whip_risk, streamability_score, two_start_bonus, save_role_certainty for pitchers. Use when you need to analyze player, compute daily_quality, compute regression index, produce player signals, run a hitter analysis, run a pitcher analysis, or prep start/sit inputs for the lineup optimizer.
mlb-playoff-scheduler
Counts MLB games per team during the Yahoo fantasy playoff window (weeks 21, 22, 23 -- Aug 17 through Sep 6, 2026) and grades the quality of each team's opponents. Emits three signals per rostered player -- playoff_games (int, max ~21), playoff_matchup_quality (0-100), holding_value (0-100) -- that drive trade-deadline and playoff-lineup decisions. Use when the user mentions playoff weeks, weeks 21-23, playoff schedule, game count, holding value, or asks whether to keep/trade a player for the playoff run. Pre-July 1 this skill returns "insufficient signal -- too early"; from July 1 onward it fires weekly.
mlb-regression-flagger
Identifies fantasy baseball players whose surface stats (wOBA, ERA, batting average) are diverging from their underlying Statcast quality (xwOBA, FIP, xBA) — emits a `regression_index` from -100 (very lucky, sell high) to +100 (very unlucky, buy low). Primary signal for buy-low/sell-high decisions on trades and waivers. Use when user mentions "buy low", "sell high", "regression candidate", "lucky", "unlucky", "xwOBA gap", "ERA-FIP gap", "BABIP", "due for regression", or is deciding whether to trade for / trade away a player based on over- or under-performance.
mlb-signal-emitter
Validates and persists signal files to the yahoo-mlb signals directory. Every MLB skill calls this skill before writing a signal. Enforces the signal-framework.md schema -- required YAML frontmatter fields (type, date, emitted_by, confidence, source_urls), range-checks numeric signals (0-100 unipolar, -100 to +100 bipolar), verifies variant_synthesis metadata, and enforces file naming. On validation failure, does not persist and routes a failure entry to mlb-decision-logger. Use when an agent or skill needs to emit a signal, validate a signal file, write to signals/YYYY-MM-DD-<type>.md, or check signal frontmatter. Triggers — "emit signal", "validate signal", "write signal file", "signal frontmatter".
mlb-trade-evaluator
Computes the full impact of a proposed MLB fantasy trade across all 10 H2H categories (R/HR/RBI/SB/OBP, K/ERA/WHIP/QS/SV), rest-of-season dollar value, positional flexibility, slot-value optionality, adverse-selection prior, and weeks 21-23 playoff impact. Produces a signed verdict (accept / counter / reject) with rationale and a specific counter if applicable. Use when user mentions "trade evaluation", "trade value", "should I accept", "trade delta", "counter offer", or pastes in a trade proposal from Yahoo. Defaults to COUNTER in the middle band — pure REJECT is reserved for clearly predatory offers.
mlb-two-start-scout
For a given fantasy week (Monday-Sunday), identifies every starting pitcher scheduled to start twice, validates both probable starts, grades each matchup against the league's Quality Starts (QS) scoring rules, and ranks the list by streamability_score. Flags bullpen-game and opener risks that nearly never produce QS. Use when user mentions "two-start pitchers", "weekly streaming", "Monday-Sunday pitcher plan", "double start", "2-start SP", or preparing the weekly streaming plan on Sunday nights.
ml-primitive-decoder
Decomposes any ML construct (attention, layer norm, softmax, convolution, dropout, contrastive loss, diffusion step, gradient descent update, cross-entropy) into the small set of linear-algebra primitives it's built from, then explains why those primitives produce the observed behavior. Includes an ablation thought experiment that asks "what would break if you removed this piece?". Use when the user asks "why does X work?", "explain attention/conv/norm intuitively", "what's actually happening in this layer", or when reading an architecture paper and a particular block doesn't make sense yet.
monte-carlo-valuation
Turns a point-estimate valuation into a distribution — samples the drivers you are least sure about from normal, lognormal, triangular, uniform or discrete-scenario distributions, re-runs the DCF engine on every draw, and reports percentiles, mean, standard deviation, the probability the value exceeds the market price, and the share of draws the engine refused as infeasible. Correlates drivers through a shared common factor. Use when running a Monte Carlo simulation or a probabilistic valuation, putting a range or confidence band around a value per share, asking how likely it is that a stock is under- or overvalued, valuing a commodity or cyclical company where one macro variable such as the oil price dominates, or turning a scenario grid into a probability-weighted expected value.
narrative-arc-mapping
Maps researched evidence onto Truby's twenty-two structural steps without fabricating the steps the evidence cannot fill. Runs the designing-principle discrimination test, step-fit triage (PRESENT / ABSENT / NOT APPLICABLE), per-slot warrant cards, the empty-slot decision table, the moral-argument spine, and the revelation-intensity audit, then stops at a tagged scene weave. Use when architecting a long-form nonfiction piece from a research corpus, structuring a post-mortem, market history, biography, or science writeup, or when user mentions Truby, 22 steps, designing principle, moral argument, revelation sequence, scene weave, or step-fit triage.
narrative-evidence-ledger
Builds the evidence ledger that narrative work is allowed to be built on, before any structure is chosen. Locks the frame (unit, denominator, window, population boundary), atomizes material into findings with evidence classes A-F and re-findable pointers, triages every causal claim L1 MECHANISM to L5 CONJECTURE with permitted and banned verb sets, runs one-way promotion from finding to claim to beat, and keeps a DEAD column of everything a veto killed. Use before outlining or drafting any evidence-based narrative, when auditing whether a draft's claims are actually sourced, when a piece needs a provenance layer for handoff, or when user mentions evidence ledger, claim ledger, provenance, sourcing, causal grading, denominator lock, cherry-picking, or circular citation.
narrative-fallacy-guard
Stops a true set of facts from being assembled into a false story. Runs the retrospective slot audit, the outcome-blind rewrite (flip test, separation test), the inevitability audit with its overshoot check, the survivorship graveyard pass, the counterfactual admissibility gate, and the expensive proportion and omission audits. Every check labels and discloses; none deletes. Use when drafting or reviewing history, post-mortems, biography, market or protocol narratives, research writeups, or any account written after the outcome was known, or when user mentions hindsight bias, narrative fallacy, survivorship bias, inevitability, halo effect, outcome bias, just-so story, teleology, or Whig history.
narrative-fidelity-audit
Runs the hard gate on invention in fact-based narrative — a bright-line refusal sweep, an interior-state provenance ladder ([A] said-so / [B] contemporaneous document / [C] behavioural inference / [D] unsourced, where any [D] blocks publication), an LLM-specific fabrication red-flag scan, a three-altitude "How do you know?" prosecution at sentence, paragraph and passage level, a subtraction-log set review, and a note on sources generated from the deviation log. Use before shipping any narrative built on real evidence — market history, incident post-mortem, biography, ML writeup, supply-chain reconstruction, science writing — or when the user mentions fact-check, fidelity audit, fabrication check, invented detail, sourcing pass, did I make this up, composite scene, note on sources, or is this defensible.
narrative-form-triage
Decides which narrative form a body of researched material can actually support, before any structure is imposed. Runs a six-question form-triage gate producing STORY NARRATIVE, EXPLANATORY NARRATIVE, MULTI-NODE GATHERING, or DO NOT NARRATE; runs the ABT (And/But/Therefore) spine diagnostic; selects a spine from a thirteen-structure table covering Truby arc, layer cake, pyramid/SCQA, OCAR, PR/FAQ, sparkline, Raskin five-slot, martini glass, drill-down, inverted pyramid and braided/mosaic; and writes an immutable spine contract with a boredom budget. Use before outlining or drafting any long-form nonfiction, report, post-mortem, market history, research writeup or case study, or when user mentions find the narrative, what's the story here, narrative arc, story structure, how should I structure this, does this have a story, or storytelling with data.
narrative-handoff-contract
Defines and validates the machine-readable contract that passes a narrative architecture between a structural agent and a drafting agent — architecture.json with evidence-backed slots, capped scene tags, gap dispositions, a DEAD column, and an escalation object for sending defects back upward. Ships a validator script so the rules are enforced rather than requested. Use when two agents or two sessions must hand narrative work to each other, when an architecture needs checking before drafting begins, when a draft must report a defect it cannot fix at its own layer, or when the user mentions handoff, contract, schema, validator, architecture.json, escalation, or "the outline and the draft have drifted apart".
narrative-opposition-web
Builds a four-corner opposition web for narrative nonfiction and stops the writer from casting whoever lost as the villain. Runs Truby's four-corner worksheet (shared central moral problem, per-corner value clusters, distinct routes of attack, corner-to-corner conflict), the best-possible-opponent audit (same goal, necessity, relentlessness, value conflict, the double, power parity, justification in the opponent's own voice), the Opponent Warrant evidence test that demotes undocumented antagonists to rivals or constraints, and a drive-section collapse check that catches a web that was decorative. Use when planning a piece with competing parties, when an antagonist feels flat or cartoonish, when the protagonist is a system rather than a person, or when user mentions opposition web, four-corner opposition, antagonist, opponent, villain, steelman the other side, character web, who is the bad guy here.
narrative-to-numbers
Builds the business story behind a valuation and connects it to the drivers that carry value — market size, growth, margin, reinvestment efficiency and risk. Tests a narrative as possible, plausible and probable, and keeps the feedback loop open. Use when starting a valuation, writing the story behind a company, setting growth or margin assumptions, sanity-checking a story against its numbers, choosing a target margin or sales-to-capital ratio, or when a valuation needs a defensible reason for its inputs.
normalize-format
Normalizes a single inbox file of any supported format (plain markdown, Claude.ai JSON export, Claude Code JSONL session, Readwise markdown/CSV highlight, transcript with timestamps or speaker labels, link capture) into a clean markdown body plus partial frontmatter (id, title, source block, word_count). Handles format-specific failure modes — JSON content-block arrays, timestamp stripping, per-highlight chunking, URL-vs-commentary separation. Use when ingesting any inbox item for the substacker Librarian. Trigger keywords — normalize, convert, parse, transcript, export, JSON, JSONL, highlight, CSV.
numbers-in-narrative
Writes quantities into prose so they land without overstating what the source supports. Applies a per-paragraph number-landing checklist (three numbers per paragraph, one per sentence, direction before magnitude, a comparison on the same screen), a unit-and-denominator lock that catches denominator drift, quantitative fidelity refusals (precision ceiling, rounding drift, percent vs percentage point, model output vs measurement), an uncertainty routing table, a declared likelihood-and-confidence ladder, and a chart-beat contract for exhibits that carry a claim. Use when drafting or editing prose that carries figures, statistics, benchmarks, forecasts or estimates, when a passage reads as a stat wall, when deciding how much precision or hedging a number can bear, or when the user mentions numbers in prose, rounding, denominator, per capita, percentage points, error bars, confidence, uncertainty, chart title, caption, or stat wall.
opener-critique
Evaluates the first 1-3 sentences of a substacker draft against the writer's signature opener patterns — confession / "I hadn't done X" / reframe / small concrete admission. Classifies opener as confession | reframe | admission | news-hook | generic-opener and flags news-hook/generic as tier-1. The opener sets the voice contract for the essay. Use on every draft. Trigger keywords — opener, hook, first sentence, opening, confession opener, news hook, generic opener.
opponent-archetype-classifier
Classifies an opposing player, manager, or agent into one of a configurable archetype set using Bayesian inference over observed behavior (roster composition, transaction pattern, lineup moves, trade activity). Domain-neutral scaffold -- callers supply the archetype taxonomy (names, priors, characteristic feature distributions) and observed features; the skill returns a normalized posterior, MAP archetype, classification confidence, feature-contribution breakdown, and best-response hints. Use when modeling opponents, classifying player types, performing Bayesian archetype inference, producing opponent posteriors, or when user mentions opponent archetype, classify opponent, Bayesian archetype inference, player type classification, opponent modeling, or archetype posterior.
option-valuation-toolkit
Prices options for valuation work — Black-Scholes with a cost-of-delay yield, binomial trees that allow early exercise, dilution-adjusted employee options for the equity bridge, equity in a heavily levered firm valued as a call on firm value, and implied volatility. Use when employee options or warrants must be subtracted before computing value per share, when a distressed or negative-earnings company's equity still trades above zero, when testing whether a patent, licence, undeveloped reserve or expansion right is a real option that deserves a premium, or when early exercise makes a European formula wrong. Triggers on option pricing, Black-Scholes, binomial tree, real options, option to delay, patent as an option, equity as a call option, distress and default probability, employee stock options, dilution, warrants, implied volatility, put-call parity.
paid-tier-readiness-check
Evaluates whether substacker has the four preconditions for launching a paid tier — enough subs, healthy engagement, a clear candidate section, writer capacity. Produces readiness score (not-ready / close / ready) with named gaps. Used when the "should we launch paid?" question is selected or at writer's explicit request. Trigger keywords — paid tier, paid readiness, monetization, Substack paid, launch paid, 1000 subscribers.
paper-cluster-by-theme
Groups a set of kept papers into 2-5 thematic clusters before synthesis, using abstract semantics + matched-keyword overlap. Names each cluster with a short noun phrase that describes what the cluster argues, not just the topic. Surfaces an "outliers" bucket for single-paper themes that don't fit. Domain-neutral - usable for any literature-scan workflow. Use after relevance filtering and before writing the synthesis report. Trigger keywords - cluster papers, group by theme, thematic clusters, paper themes, organize papers.
paper-relevance-filter
Scores a candidate paper against a keyword watchlist and a relevance-criteria document, returning KEEP/DROP/REVIEW with a one-line rationale and a 0-100 relevance score. Combines keyword-match strength, criteria-fit, and a historical-context check (was this paper or its preprint already covered in a recent digest). Domain-neutral - usable for any literature-scan workflow. Use after fetching candidate papers from bioRxiv, medRxiv, or PubMed and before clustering or synthesis. Trigger keywords - paper relevance, filter papers, keep or drop, score papers, relevance rationale.
paper-three-pass-extraction
Domain-neutral methodology for autonomously extracting structured notes from a single academic paper via three escalating passes. Pass 1 (inspectional, ~10-15 min) reads title, abstract, intro, section headings, conclusion, references at a glance, then applies the Five Cs framework (Category, Context, Correctness, Contributions, Clarity). Pass 2 (content grasp, ~30-60 min) reads the full paper skipping proofs, answers main-argument / Big-Question / hypotheses / figure-by-figure / references / confusions. Pass 3 (deep understanding, ~1-4 hours, reserved for important papers) virtually re-implements, challenges every assumption, identifies what is NOT said, asks the falsifiability question. The methodology is internal to the agent applying it - questions are answered against the paper's content, never asked of the operator. Use when an extraction agent needs to convert dense academic prose into structured machine-and-human-readable notes - bio papers, CS papers, ML papers, statistics, math, any field.
paragraph-rhythm-check
Checks paragraph rhythm in a substacker draft — long/short mix, one-sentence paragraph at pivots, no walls, avoid monotony. Flags drafts where >3 consecutive paragraphs share the same length bucket, where the pivot lacks a one-sentence paragraph, or where any paragraph exceeds 120 words. Use in the Editor's structural pass. Trigger keywords — rhythm, paragraph length, wall of text, one-sentence paragraph, pivot, monotone.
payout-policy-analysis
Assesses whether a company returns the right amount of cash to shareholders. Computes FCFE over a history under three debt assumptions, compares it against dividends plus buybacks to give the cash surplus or deficit, places the firm in the dividend matrix of affordability against project quality, projects forward FCFE and buyback capacity, and benchmarks payout ratio and dividend yield against peers and the market. Handles bank FCFE from regulatory capital. Use for dividend policy, payout ratio, dividend yield, potential dividends, FCFE, cash returned, buybacks, share repurchase capacity, excess cash, dividend cut or increase, cash accumulator or overpayer, or the dividend matrix.
pdf-statement-parser
Parses a single financial statement PDF (checking, savings, credit card, brokerage, 401k, HSA, mortgage, tax form) and emits a normalized JSON record with institution, account mask, statement period, opening/closing balances, line-item transactions or holdings, and a confidence score. Use when extracting structured data from a bank, brokerage, retirement, or HSA PDF statement, when ingesting a drop of household finance documents, or when user mentions parsing a statement, extracting transactions from a PDF, or normalizing statement data.
per-section-tracking
Breaks down weekly and trailing-4-week substacker performance per Substack section, keyed on section tags in corpus/published/ and section-map.md. Reports opens, clicks, subs-attributable-to-section per section with ≥3 posts. Skips if section-map has <2 sections. Feeds Curator with pruning candidates (sections with 4-week median z ≤ -1.0). Use when section-map has ≥2 live sections. Trigger keywords — per-section, section performance, section metrics, section pruning, differential engagement.
platform-voice-check
Runs a voice-fidelity audit on each of the four substacker platform outputs (Substack Note, X thread, LinkedIn post, cross-post blurb) before reporting Distribution Translator completion. Checks for voice-don'ts (banned vocabulary, emoji, generic openers, marketing math without source), voice-do compliance (paper attribution preserved, hedges preserved, em-dash reframes present), platform-specific tonal shifts. Emits voice-check.md with pass/fail per artifact. Trigger keywords — platform voice check, voice-check, gate, distribution voice, slop-leak check.
portfolio-drift-rebalancer
Aggregates investment holdings across taxable brokerage, 401k, and HSA into a single asset-allocation view, computes drift versus a target allocation, and produces a tax-efficient rebalance proposal that prefers tax-advantaged accounts for the trades and never executes. Flags drift over 5 percentage points and free-money issues like missed 401k employer match. Use when reviewing portfolio allocation, planning a rebalance, computing drift, or when user mentions asset allocation, drift, rebalancing proposal, or 401k match.
product-hiding-scan
Scans the substacker published corpus for clusters of posts that could become a product — a course, a book, a cohort, or a consulting offer. Produces at most 2 candidates with evidence + audience signal, or an honest "not yet" verdict if nothing qualifies. Typically fires once the writer has 30+ posts. Trigger keywords — product hiding, course from essays, book from essays, corpus to product, product scan.
project-investment-analysis
Evaluates a discrete investment, project or acquisition from its cash flow stream — NPV, IRR with every root reported when the stream has more than one, MIRR, profitability index and project selection under a capital budget, equivalent annuities and replication for unequal lives, payback and discounted payback, project return on capital and EVA, synergy value with the ceiling price it supports, the value of control and its expected value, the four-number acid test for a deal, and control premiums and minority discounts. Use when deciding whether to take a project, ranking competing projects, comparing projects with different lives, sizing a capital budget, testing whether a stream is truly incremental, valuing synergy or control, pricing a majority or minority stake, or setting the maximum price for an acquisition.
propose-counterfactual
Produces the counterfactual framing in an Intuition Builder 5-set — "what if this component were not here?" Reveals the function of a technical element by subtracting it and observing what breaks. Uses Pearl's causal ladder (counterfactual = level 3) as the theoretical spine. Use as the 5th archetype slot of generate-analogy-set, or invoked standalone when the writer wants to build intuition for why a specific element exists. Trigger keywords — counterfactual, what if not, remove, subtract, reveal function, why does this exist.
propose-section
Converts one candidate cluster from cluster-corpus-by-theme into a named, promised section proposal ready for writer review. Calls write-section-promise for the one-sentence promise. Rates fit confidence (high / medium / low / provisional) and flags borderline posts. Use once per cluster that passes ≥3-post threshold. Trigger keywords — propose section, section proposal, new section candidate.
prose-force-and-rhythm
Runs Jack Hart's Wordcraft line passes in strict order (Structure, Force, Brevity, Clarity, Rhythm, Humanity, Color, Voice, Mechanics) followed by a slop audit, one pass per edit class, with a claim-strength invariant that stops verb strengthening and hedge cutting from silently overclaiming. Enforces upward escalation instead of downward compensation, a protected-hedge list, a clarity split log the rhythm pass may not undo, and rhythm metrics reported as diagnostics rather than optimized. Use when line-editing a draft, tightening flabby prose, fixing weak verbs or monotonous sentence rhythm, de-slopping AI-sounding copy, or when user mentions line edit, force pass, punch it up, tighten this, passive voice, wordy, sentence variety, sounds like AI, burstiness, or Wordcraft.
quarterly-zoomout
Synthesizes 13 weeks of substacker Growth Analyst reports + the most recent Curator review + a meta-scan of the published corpus into a 400-700 word narrative that names the quarter's shape — what happened, what changed, what held steady, what surprised. Used by the Growth Strategist at the opening of every review. Trigger keywords — quarterly, zoomout, quarter narrative, rollup, what happened this quarter.
rank-by-user-fit
Scores and ranks substacker Trend Scout annotated candidates against voice-profile and goals, producing a top-10 keep list and an explicit drop list with reasons. Weighted-sum scoring across intuition-density fit, goal alignment, dedup penalty, source reliability, freshness. Produces the digest's keeps and drops sections. Use after cross-ref-topic-ledger. Trigger keywords — rank, fit score, user fit, keep list, drop list, signal weight.
readability-check
Scores prose with Flesch Reading Ease, Flesch-Kincaid Grade, SMOG, Gunning Fog, and Dale-Chall, reports every score on one shared grade-band scale, and rewrites the sentences that fail. Runs on markdown files or on piped draft text before it is sent, and can run automatically through Claude Code hooks. Use before delivering any substantial written output, when a draft reads as convoluted or bloated, when a document must hit a reading-level target, or when checking a folder of documents for prose quality. Trigger keywords — readability, reading level, Flesch, Flesch-Kincaid, SMOG, Gunning Fog, Dale-Chall, grade level, hard to read, convoluted, dense prose, plain language, reading ease.
reader-first-prose
Rewrites expository prose for a reader meeting the subject for the first time, not an insider who already shares the writer's knowledge. Enforces introduce-before-use (every entity, term and acronym defined on first mention, in an order a newcomer can follow), grounds or cuts every metaphor in the same breath it appears, converts compressed or nominalized logic into a plain if-then, and kills the two loudest machine tells, the em dash and the terse two-beat antithesis ("X. Not Y."). Carries an honesty pass so the prose never out-claims its evidence, marking inference as inference and preserving every number exactly. Use when a draft assumes knowledge the reader lacks, reads as insider or "clever", name-drops terms before defining them, leans on unexplained metaphor, or sounds AI-written; or when the user mentions first-time reader, plain language, define before use, sounds like AI, em dash, too clever, or jargon. Complements ladder-of-abstraction, slop-detector and narrative-fidelity-audit.
recommend-prune
Recommends structural cleanups for the substacker section map — sections to retire, sections to merge, posts to reassign. Applies under-filled, stale, and overlapping heuristics. Writes proposals with reasons-to-reject (steelman counter). Does not execute. Use once per Curator run, after drift audit. Trigger keywords — prune, retire section, merge sections, reassign post, cleanup.
recurring-charge-detector
Identifies recurring charges (subscriptions, monthly bills, biweekly paychecks) from a transaction history by clustering same-merchant transactions of similar amount on a regular cadence, requiring at least 3 confirming occurrences before promoting a candidate to active status. Detects new recurring charges, dormant subscriptions (missed expected dates), and amount drift, and computes annualized cost. Use when auditing subscriptions, building a recurring bills calendar, computing cash-flow forecast inputs, or when user mentions subscription audit, recurring detection, dormant subscription, or annualized cost.
relative-valuation-toolkit
Prices a company against peers and the market with multiples — builds PE, PEG, PBV, EV/EBITDA, EV/EBIT, EV/Sales and EV/Invested Capital with the numerator/denominator consistency rule enforced, computes peer medians and quartiles, fits an ordinary-least-squares regression of a multiple on its companion variables for a sector or the whole market, reports predicted versus actual under and over valuation, and derives the intrinsic multiple from DCF fundamentals. Prices a conglomerate division by division with a sum of the parts, and values cross-holdings and minority interests. Bundles Damodaran's regional pricing regressions and multiple distributions. Use for relative valuation, comparable company analysis, trading comps, sector or market multiple regressions, justified multiples, PEG screens, sum-of-the-parts or break-up analysis, conglomerate discounts, cross-holdings and minority interests, or when asked whether a stock is cheap on its multiple.
scene-construction-scam
Builds scenes that are reported rather than generated, by running a four-slot SCAM qualification gate (Setting, Character, Action, Meaning) with a source required per slot, a scene floor and ceiling, the 1-of-20 telling-detail cut with a provenance veto, the RUE pass, and a scene/summary narrative-distance audit against per-form ratio targets. Every technique has a person variant and a system variant (market, protocol, institution, codebase, supply chain). Use when turning research notes into a scene, opening a section with a moment, deciding whether a passage is a scene or summary, or auditing whether a vivid paragraph is actually sourced, or when user mentions scene, SCAM, show don't tell, telling detail, scene vs summary, summary in costume, establishing shot, make this vivid, or in medias res.
score-intuition-density
Computes a 0-10 intuition-density score for a seed body using 8 concrete measurable signals — analogy presence, concrete worked example, counterfactual offered, reframe against default, biology-to-AI transfer, question posed, calibrated hedge, math-to-metaphor handoff. Emits both the numeric score and the list of triggered signals for auditability. Use after topic tagging to enrich seed frontmatter in the substacker Librarian pipeline. Trigger keywords — intuition density, score, signals, analogy count, worked example, density proxy.
search-corpus
Answers "what have I already thought about X?" by searching the substacker corpus (seeds, drafts, published) for seeds matching a topic, keyword, analogy, or author. Returns a ranked list of seeds with id, title, status, density score, and a one-line excerpt. Use when another agent (Intuition Builder, Editor) needs prior thinking before generating new material, or when the writer asks "have I written about X." Trigger keywords — search, find, what have I, already thought, prior work, precedent, have I written about.
section-break-check
Verifies the section-break style in a substacker draft matches the post register — asterisks (* * *) for essayistic posts under 2500 words, H2 for methodology / how-to / technical posts. Flags mixed registers (H2 in a reflective essay, asterisks in a structured how-to). Per the style-guide rhythm rule. Use every draft. Trigger keywords — section break, asterisk, H2, headers, register, essayistic vs methodology.
section-portfolio-assessment
Classifies each substacker section as healthy / drifting / candidate-for-prune based on post volume, engagement trend, and niche alignment. Produces table + 2-4 paragraph narrative. Used in every quarterly review. Trigger keywords — portfolio, section health, healthy drifting prune, section assessment, which section is carrying.
skill-construction
Methodology for building a properly structured Claude Code skill (SKILL.md + optional resources + evaluation rubric) from extracted components. Assesses complexity (Level 1 simple - SKILL.md only; Level 2 moderate - SKILL.md plus 1-3 resources; Level 3 complex - SKILL.md plus 4-8 resources), plans the resource grouping, drafts SKILL.md following Anthropic's authoring best practices (concise frontmatter with what + when triggers, body under 500 lines, progressive disclosure to resource files one level deep, workflow checklists), and constructs an evaluation rubric. Use when extracted components and a synthesis verdict are in hand and the next step is to materialize them as a skill. Trigger keywords - construct skill, build SKILL.md, skill construction, skill scaffolding, generate skill files.
slop-detector
Scans a substacker draft for 10 signatures of AI-generated explainer slop — meta-framing openers ("In this post"), list-heavy argument, nominalization clusters, generic examples lacking first-person texture, prompt-residue phrases ("Let's break this down"), buzzword stuffing, outline-shaped paragraphs, hedge clusters, flattened uncertainty. Use when a draft "feels generic" even after voice-check passes. Trigger keywords — slop, AI-written, generic, template, meta-framing, zombie nouns, prompt residue, outline-shaped.
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